Supervisory adaptive fuzzy sliding mode control with optimal Jaya based fuzzy PID sliding surface for a planer cable robot

Aghaseyedabdollah, Mohammadhossein; Abedi, Mostafa; Pourgholi, Mahdi

doi:10.1007/s00500-022-07237-y

Cited by 7 publications

(2 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hosseini et al [47] designed a nonlinear PD controller for cable-driven parallel robots in joint space so that the robot can track the reference trajectory quickly and accurately, while the stability of the closed-loop system was examined through Lyapunov direct method. Aghaseyedabdollah et al [48] discussed the design of supervisory adaptive fuzzy sliding mode control with the fuzzy PID sliding surface for a planar cable-driven parallel robot. Inel et al [49] addressed a nonlinear continuous-time generalized predictive control for a planar cable-driven parallel robot.…”

Section: Pick-and-place Trajectory Tracking Controlmentioning

confidence: 99%

Pick–and–Place Trajectory Planning and Robust Adaptive Fuzzy Tracking Control for Cable–Based Gangue–Sorting Robots with Model Uncertainties and External Disturbances

et al. 2022

View full text Add to dashboard Cite

A suspended cable−based parallel robot (CBPR) composed of four cables and an end−grab is employed in a pick−and−place operation of moving target gangues (MTGs) with different shapes, sizes, and masses. This paper focuses on two special problems of pick−and−place trajectory planning and trajectory tracking control of the cable−based gangue−sorting robot in the operation space. First, the kinematic and dynamic models for the cable−based gangue−sorting robots are presented in the presence of model uncertainties and unknown external disturbances. Second, to improve the sorting accuracy and efficiency of sorting system with cable−based gangue−sorting robot, a four-phase pick−and−place trajectory planning scheme based on S-shaped acceleration/deceleration algorithm and quintic polynomial trajectory planning method is proposed, and moreover, a robust adaptive fuzzy tracking control strategy is presented against inevitable uncertainties and unknown external disturbances for trajectory tracking control of the cable−based gangue−sorting robot, where the stability of a closed-loop control scheme is proved with Lyapunov stability theory. Finally, the performances of pick−and−place trajectory planning scheme and robust adaptive tracking control strategy are evaluated through different numerical simulations within Matlab software. The simulation results show smoothness and continuity of pick−and−place trajectory for the end−grab as well as the effectiveness and efficiency to guarantee a stable and accurate pick−and−place trajectory tracking process even in the presence of various uncertainties and external disturbances. The pick−and−place trajectory generation scheme and robust adaptive tracking control strategy proposed in this paper lay the foundation for accurate sorting of MTGs with the robot.

show abstract

Section: Pick-and-place Trajectory Tracking Controlmentioning

confidence: 99%

Pick–and–Place Trajectory Planning and Robust Adaptive Fuzzy Tracking Control for Cable–Based Gangue–Sorting Robots with Model Uncertainties and External Disturbances

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In the field of control engineering, PID (Proportional-Integral-Derivative) controller is a classical feedback control algorithm. It is widely used in industrial control systems [1][2][3][4][5][6][7].The PID controller regulates the output of the system by means of three components: proportional, integral and differential. to achieve precise control of the target value.…”

Section: Introductionmentioning

confidence: 99%

A Control Method for Improved Fuzzy PID of GSOM for Fish Scale Evolution

Wang,

Cui,

Sui

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Fuzzy PID control is a control method with good adaptability and stability in complex environments. It is used to achieve precise regulation and stable control of the system. In this paper, a fish scale evolution GSOM is proposed to improve the control method of fuzzy PID. Firstly, the fish scale regulation system is established and the differential evolution theory is introduced to realize the evolutionary upgrading of the system. Secondly, the GSOM module is introduced. The system is optimized by self-organized mapping neural network to achieve dynamic regulation of polymorphic inputs. Meanwhile, the fuzzy rule base and parameter regulation mechanism in fuzzy PID control are dynamically optimized. Improve the performance of the control system. Finally, the control method of improved fuzzy PID for fish scale evolution GSOM is simulated using MATLAB. The simulation experiments also compare several traditional PID control methods. The comparison indexes include stability, robustness, control accuracy and feedback output effect. The results show that the method in this paper is more stable and has fewer iterations when facing the dynamic input environment. The tracking error and control output of the controller system are significantly improved. It has good feedback output effect, solves the saturation problem and has higher control accuracy.

show abstract

Adaptive-optimal MIMO nonsingular terminal sliding mode control of twin-rotor helicopter system: meta-heuristics and super-twisting based control approach

Rezoug,

Messah,

Messaoud

et al. 2024

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

The novelty of the proposed control approach lies in hybridization of control technique based on Nonsingular Terminal Sliding Mode (NTSM) Control, metaheuristic optimization algorithms and adaptive super-twisting based on Lyapunov stability analysis for controlling Quanser Aero simulator helicopter. Firstly, the he NTSM and NTSM Super Twisting (NTSTW) controllers are designed Followed by optimization of the designed controllers using Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA) and Ant Lion Optimizer (ALO). Qualitative and quantitative comparisons between the obtained optimized controllers is then thoroughly analyzed. Results confirmed that the Optimized NTSTW (O-NTSTW) based on GWO demonstrated overperformance compared with other controllers. In order to achieve superior performance with robustness, this controller is hybridized with an adaptive Lyapunov super-twisting algorithm resulting in a new controller Adaptive O-NTSTW (AO-NTSTW). Visualization using ROS-Gazebo is done while validating AO-NTSTW and O-NTSTW.Simulation results demonstrated the effectiveness and the superiority of AO-NTSTW compared to O-NTSTW.

show abstract

Supervisory adaptive fuzzy sliding mode control with optimal Jaya based fuzzy PID sliding surface for a planer cable robot

Cited by 7 publications

References 41 publications

Pick–and–Place Trajectory Planning and Robust Adaptive Fuzzy Tracking Control for Cable–Based Gangue–Sorting Robots with Model Uncertainties and External Disturbances

Pick–and–Place Trajectory Planning and Robust Adaptive Fuzzy Tracking Control for Cable–Based Gangue–Sorting Robots with Model Uncertainties and External Disturbances

A Control Method for Improved Fuzzy PID of GSOM for Fish Scale Evolution

Adaptive-optimal MIMO nonsingular terminal sliding mode control of twin-rotor helicopter system: meta-heuristics and super-twisting based control approach

Contact Info

Product

Resources

About